The present invention relates to a method of enhancing colour images.
Digital radiographic images are acquired with a large dynamic range (usually 12 bits per pixel). Because the human visual system is not able to distinguish all the available grey level differences and because the image has to be brought back to 8 bits per pixel for printing and displaying, post-processing of the image is often necessary.
Multi-resolution image enhancement is being used routinely nowadays for processing of digital radiographs, i.e. for grey tone images. A multi-scale image enhancement method for radiographic images has for example been described in European patent 527 525 and European patent application 1 001 370.
An iterative processing method of the above-described kind has been described in European patent application 610 603.
As acquisition techniques improve for all kinds of images, the need for effective dynamic range compression still increases.
For colour photographic images, especially for those taken in outdoor scenes, one is very often confronted with a very wide dynamic range. When reproduced this often results in an image having areas that are too dark or too light.
Effective dynamic range compression without loss of important information is then required. As many different colours as possible have to be visualised.
Especially for photographic images it is furthermore unacceptable that the applied image processing wound result in an unnatural appearance of the processed colour image
In the article xe2x80x98Multiscale color image enhancementxe2x80x99, by Toet A. in Pattern Recognition Letters, NL, North Holland Publ. Amsterdam, Vol. 13, No. 3, (Mar. 1, 1992), a multiscale image decomposition method has been disclosed for application to color images.
In this method the luminance and saturation components of an image are first decomposed into contrast detail images of different spatial scales. The contrast is defined here as the ratio of the image or a low resolution version of the image and a successive lower resolution version of the image. Next, a new set of multi-scale luminance contrast primitives is then constructed by modulating the original luminance primitives at every location in the image and at every spatial scale by their corresponding saturation contrast primitives. Reconstruction of the color image from the resulting set of multiscale primitives provides a representation of the original image in which local luminance contrast is enhanced at all resolution levels.
It is an object of the present invention to provide a method for enhancing the image quality of colour images.
The above mentioned object is realised by an image processing method as described in claim 1. Specific features for preferred embodiments of the invention are disclosed in the dependent claims.
The method of the present invention is advantageous in that effective dynamic range compression can be obtained in combination with subtle feature enhancement.
The method of the present invention comprises the steps of
decomposing at least one of the colour component images of a colour image into a multi-resolution image representation comprising bandpass detail images at multiple resolution levels and a residual image,
modifying the multi-resolution image representation of at least one colour component image at at least one resolution level so as to obtain (a) modified multi-resolution image representation(s),
reconstructing said colour component image(s) from the multi-resolution representation(s) by applying a reconstruction algorithm to the residual image and the modified and unmodified bandpass detail images of the respective colour component image(s), said reconstruction algorithm being such that if it were applied to the residual image and unmodified bandpass detail images of a colour component image, the colour component image or an approximation thereof would be obtained.
Preferably the modification is non-linear. At least one non-linear modifying function is applied to the detail image(s)
In a specific embodiment the multi-resolution image representation(s) is/are modified by multiplying the value of a detail image at pixel i and at resolution level j with a factor which is obtained by evaluating a non-linear modifying function in an argument value which depends on pixel values of detail images of said colour components at pixel i and resolution level j.
The multi-resolution image representation(s) is/are for example modified by multiplying the value of a detail image at pixel i and at resolution level j with a factor which is obtained by evaluating a non-linear modifying function in an argument value which depends on pixel values of detail images of said colour components at resolution level j and pixel i.
In one embodiment the multi-resolution representation comprises directional bandpass detail images. The multi-resolution representation is e.g. a multi-resolution gradient representation.
In a specific embodiment the argument of the modifying function is the norm of the colour gradient in a specific pixel and specified resolution level.
The modifying function may for example have the form set out in claim 8. It may depend on a pixel value in the vaginal image.
Further details on the modifying function are described further on.
The colour component images may be defined in a perceptual colour space such as the L, u, v colour space.
A gamut may be defined and the colour component images may be re-scaled to that defined gamut after reconstruction. The gamut may be the gamut of the original image.
The present invention as well as specific and/or preferred embodiments thereof will be explained in detail with reference to the accompanying drawings.